Optimization of Image Preprocessing Techniques Using Simplified Algorithms for Parking Slot Detection.
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| Title: | Optimization of Image Preprocessing Techniques Using Simplified Algorithms for Parking Slot Detection. |
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| Authors: | Anwar, Herlina1 herlina@unhas.ac.id, Areni, Intan Sari2 intan@unhas.ac.id, Indrabayu3 indrabayu@unhas.ac.id, Ramdhani Fadhil, Muh. Wira4 fadhilmwr21d@student.unhas.ac.id |
| Source: | IAENG International Journal of Computer Science. Jan2026, Vol. 53 Issue 1, p286-295. 10p. |
| Subjects: | Image processing, Statistical accuracy, Image enhancement (Imaging systems), Smart parking systems, Real-time computing |
| Abstract: | Urban parking challenges are escalating because of the rapid urbanization and increasing vehicle ownership, highlighting the need for intelligent parking solutions. This study compares two image preprocessing techniques, traditional image processing and background subtraction, for the detection of empty parking slots. The traditional approach applies grayscale conversion, Gaussian filtering, thresholding, and dilation to enhance the object contours and suppress noise. By contrast, the background subtraction method isolates dynamic changes by computing pixel-level differences against a static reference image. Both techniques were evaluated in two real-life parking environments, namely street and structured parking, considering environmental challenges, such as shadows, pedestrian activity, and surface irregularities. The experimental results show that the Background Subtraction Method consistently outperformed the Traditional Image Processing Method, achieving an average accuracy of 98.44%, compared to 92.73% for the traditional approach across all tested thresholds. Furthermore, the Background Subtraction Method demonstrated superior computational efficiency with an average processing time of 0.0445 seconds per frame (13.92 FPS), nearly twice as fast as the Traditional Image Processing Method which required 0.0878 seconds per frame (8.70 FPS). Although the performance of traditional image processing is relatively close to that of background subtraction, both methods demonstrate strong capability. However, background subtraction offers distinct advantages by providing both higher accuracy and significantly reduced computational cost, making it more suitable for real-time applications. [ABSTRACT FROM AUTHOR] |
| Copyright of IAENG International Journal of Computer Science is the property of International Association of Engineers (IAENG) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 190604263 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Optimization of Image Preprocessing Techniques Using Simplified Algorithms for Parking Slot Detection. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Anwar%2C+Herlina%22">Anwar, Herlina</searchLink><relatesTo>1</relatesTo><i> herlina@unhas.ac.id</i><br /><searchLink fieldCode="AR" term="%22Areni%2C+Intan+Sari%22">Areni, Intan Sari</searchLink><relatesTo>2</relatesTo><i> intan@unhas.ac.id</i><br /><searchLink fieldCode="AR" term="%22Indrabayu%22">Indrabayu</searchLink><relatesTo>3</relatesTo><i> indrabayu@unhas.ac.id</i><br /><searchLink fieldCode="AR" term="%22Ramdhani+Fadhil%2C+Muh%2E+Wira%22">Ramdhani Fadhil, Muh. Wira</searchLink><relatesTo>4</relatesTo><i> fadhilmwr21d@student.unhas.ac.id</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22IAENG+International+Journal+of+Computer+Science%22">IAENG International Journal of Computer Science</searchLink>. Jan2026, Vol. 53 Issue 1, p286-295. 10p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Image+processing%22">Image processing</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+accuracy%22">Statistical accuracy</searchLink><br /><searchLink fieldCode="DE" term="%22Image+enhancement+%28Imaging+systems%29%22">Image enhancement (Imaging systems)</searchLink><br /><searchLink fieldCode="DE" term="%22Smart+parking+systems%22">Smart parking systems</searchLink><br /><searchLink fieldCode="DE" term="%22Real-time+computing%22">Real-time computing</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Urban parking challenges are escalating because of the rapid urbanization and increasing vehicle ownership, highlighting the need for intelligent parking solutions. This study compares two image preprocessing techniques, traditional image processing and background subtraction, for the detection of empty parking slots. The traditional approach applies grayscale conversion, Gaussian filtering, thresholding, and dilation to enhance the object contours and suppress noise. By contrast, the background subtraction method isolates dynamic changes by computing pixel-level differences against a static reference image. Both techniques were evaluated in two real-life parking environments, namely street and structured parking, considering environmental challenges, such as shadows, pedestrian activity, and surface irregularities. The experimental results show that the Background Subtraction Method consistently outperformed the Traditional Image Processing Method, achieving an average accuracy of 98.44%, compared to 92.73% for the traditional approach across all tested thresholds. Furthermore, the Background Subtraction Method demonstrated superior computational efficiency with an average processing time of 0.0445 seconds per frame (13.92 FPS), nearly twice as fast as the Traditional Image Processing Method which required 0.0878 seconds per frame (8.70 FPS). Although the performance of traditional image processing is relatively close to that of background subtraction, both methods demonstrate strong capability. However, background subtraction offers distinct advantages by providing both higher accuracy and significantly reduced computational cost, making it more suitable for real-time applications. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of IAENG International Journal of Computer Science is the property of International Association of Engineers (IAENG) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 10 StartPage: 286 Subjects: – SubjectFull: Image processing Type: general – SubjectFull: Statistical accuracy Type: general – SubjectFull: Image enhancement (Imaging systems) Type: general – SubjectFull: Smart parking systems Type: general – SubjectFull: Real-time computing Type: general Titles: – TitleFull: Optimization of Image Preprocessing Techniques Using Simplified Algorithms for Parking Slot Detection. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Anwar, Herlina – PersonEntity: Name: NameFull: Areni, Intan Sari – PersonEntity: Name: NameFull: Indrabayu – PersonEntity: Name: NameFull: Ramdhani Fadhil, Muh. Wira IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Text: Jan2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 1819656X Numbering: – Type: volume Value: 53 – Type: issue Value: 1 Titles: – TitleFull: IAENG International Journal of Computer Science Type: main |
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